Flexible monitoring of mechatronic technological machines
https://doi.org/10.12737/22149
Abstract
He work objective is the presentation of the main aspects of the flexible monitoring system of the mechatronic processing machines state including the multioperational computer-controlled machines. The basis of such a system is considered the abandonment of the response strategy to failure in favor of a flexible proactive and predictive maintenance. A variant of the flexible system implementation based on the intelligent technologies is proposed. The basic principles of the flexible monitoring system that makes possible the adaptive capability to the unfolding situation are proved. They include combined neuro-fuzzy subsystems to implement such features as the selection of various types of technical maintenance, the determination of the urgency of its carrying out, the choice of the service facilities, and making the recommendations on the feasibility of the technological mode change at work within the border area of the machine runnability.
Keywords
гибкий мониторинг состояния,
мехатронные технологические машины,
многооперационные станки,
нечеткая граница работоспособности,
система e-Mindmachine,
нейронечеткая модель,
flexible condition monitoring,
mechatronic technological machines,
multioperational machines,
fuzzy border operability,
e-Mindmachine system,
neuro-fuzzy model
About the Authors
Andrew K. Tugengold
Don State Technical University
Russian Federation
Russian Federation
Roman N. Voloshin
Don State Technical University
Russian Federation
Russian Federation
References
1. Lee, J., et al. Intelligent prognostics tools and e-maintenance. Computers in Industry, 2006, no. 57, pp. 476–489.
2. ISO 13372:2012 Condition monitoring and diagnostics of machines. International Organization for Standardization. Available at: http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?snumber=52256 (accessed: 19.11.16).
3. Maltsev, А.I., Maltsev, А.A. Monitoring tekhnicheskogo sostoyaniya krupnykh mashin. [Monitoring of technical condition of large machines.] Elektrostal: DAMO, 1998, 62 p. (in Russian).
4. Djurdjanovic, D., Lee, J., Ni, J. Watchdog Agent — an infotronics-based prognostics approach for product performance degradation assessment and prediction. Advanced Engineering Informatics, 2003, no. 17 (3), pp. 109–125.
5. Moore, W.-J., Starr, A.-G. An intelligent maintenance system for continuous cost-based prioritisation of maintenance activities. Computers in Industry, 2006, no. 6, pp. 595–606 (Elsevier. Special issue on E-maintenance).
6. Wonderware System Platform. Condition based monitoring 3.0. Available at: www.wonderware.ru (accessed: 12.12.15).
7. Kruglova, Т.N., Glebov, N.A. Diagnostirovanie i prognozirovanie tekhnicheskogo sostoyaniya mekhatronnykh moduley dvizheniya tekhnologicheskogo oborudovaniya. [Diagnosis and forecasting of the technical condition of mechatronic modules of processing equipment movement.] Novocherkassk: YuRGTU (NPI), 2011, 119 p. (in Russian).
8. Emmanouilidis, C. et al. E-Maintenance update: the road to success for modern industry. Proceedings of the 24th International Congress on condition monitoring and diagnostic engineering management. Stavanger, 201, 423 p.
9. Tugengold, А.К. , Voloshin, R.N., Yushchenko, S.V. Modul' E-Mindmachine v intellektual'noy sisteme monitoringa stanka. [Module E-Mindmachine in the intellectual monitoring system of the machine.] International Research Journal, 2015, no. 9 (40), part 2, pp. 100–102 (in Russian).
10. GOST R ISO 17359-2009. Kontrol' sostoyaniya i diagnostika mashin. Obshchee rukovodstvo po organizatsii kontrolya sostoyaniya i diagnostirovaniya: GOST R ISO 17359-2009. [Condition monitoring and diagnosis of machines. General Guidelines (IDT).] CIS Council for Standardization, Metrology and Certification, Moscow: Standartinform, 2010, 20 p. (in Russian).
11. Tugengold, А.К., Voloshin, R.N., Yushchenko, S.V. Monitoring sostoyaniya mnogooperatsionnykh stankov na baze kontseptsii e-Mindmachine. [Monitoring of multioperational machines based on the concept of e-MIND MACHINE.] Vestnik of DSTU, 2016, vol. 16, no. 1 (84), pp. 77–86 (in Russian).
12. Tugengold, А.К., Lukyanov, E.A. Intellektual'nye funktsii i upravlenie avtonomnymi tekhnologicheskimi mekhatronnymi ob''ektami. [Intelligent features and management of autonomous technological mechatronic objects.] Rostov-in- Don: DSTU Publ. Centre, 2013, 203 p. (in Russian).
13. Zhernakov, S.V. Primenenie tekhnologii neyronnykh setey dlya diagnostiki tekhnicheskogo sostoyaniya aviatsionnykh dvigateley. [Application of neural network technology for the diagnosis of technical condition of aircraft engines.] Intellektual'nye sistemy v proizvodstve, 2006, no. 2, pp. 70–83 с. (in Russian).
14. Nikitin, Y.R., Abramov, I.V. O postroenii sistemy diagnostirovaniya stankov s ChPU. [Designing of CNC Machines, Diagnosing system.] Mechatronics, Automation, Control, 2011, no. 4, pp. 32–35 (in Russian).
Review
For citations:
Tugengold A.K., Voloshin R.N. Flexible monitoring of mechatronic technological machines. Vestnik of Don State Technical University. 2016;16(4):51-58. (In Russ.) https://doi.org/10.12737/22149
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